Applied multivariate statistical analysis
Applied multivariate statistical analysis
The SimpleScalar tool set, version 2.0
ACM SIGARCH Computer Architecture News
Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
Saving energy with architectural and frequency adaptations for multimedia applications
Proceedings of the 34th annual ACM/IEEE international symposium on Microarchitecture
Contents provider-assisted dynamic voltage scaling for low energy multimedia applications
Proceedings of the 2002 international symposium on Low power electronics and design
Control-theoretic dynamic frequency and voltage scaling for multimedia workloads
CASES '02 Proceedings of the 2002 international conference on Compilers, architecture, and synthesis for embedded systems
Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Basic Block Distribution Analysis to Find Periodic Behavior and Simulation Points in Applications
Proceedings of the 2001 International Conference on Parallel Architectures and Compilation Techniques
Frame-based dynamic voltage and frequency scaling for a MPEG decoder
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Using offline bitstream analysis for power-aware video decoding in portable devices
Proceedings of the 13th annual ACM international conference on Multimedia
Resource prediction for media stream decoding
Proceedings of the conference on Design, automation and test in Europe
Exploiting media stream similarity for energy-efficient decoding and resource prediction
ACM Transactions on Embedded Computing Systems (TECS)
Implementing real-time video decoding on multimedia processors by complexity prediction techniques
IEEE Transactions on Consumer Electronics
H.264/AVC baseline profile decoder complexity analysis
IEEE Transactions on Circuits and Systems for Video Technology
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Scenario-based design exploits the time-varying execution behavior of applications by dynamically adapting the system on which they run. This is a particularly interesting design methodology for media applications with soft realtime constraints such as decoders: frames can be classified into scenarios based on their decode complexity, and the system can be configured on a per-scenario basis such that energy consumption is reduced while still meeting the deadlines. At the foundation of scenario-based design lies the ability to identify scenarios, or recurring modes of operation with similar run time characteristics. There are two opposite ends to scenario identification. Some researchers have proposed techniques that, based on domain knowledge, identify hardware-independent scenarios in a media input stream. At the other end, other researchers have proposed techniques that identify hardware-dependent scenarios in a (semi-) automated way. This paper proposes a scenario identification approach that bridges both opposite ends, and finds hardware-independent scenarios in an automated way. It does so by computing execution profiles on a per-frame basis that capture the application's code execution patterns. We find that Edge Vectors (EVs) are more accurate than Basic Block Vectors (BBVs) at capturing the variation in frame-level decode complexity. The complexity of the proposed automated scenario identification is comparable to existing hardware-dependent scenario identification approaches, yet the scenarios can be used across hardware implementations.